We want to invite you to help build world's SuperComputer

#1
Hi everyone,

I’m the founder of Good Ai Lab and we have just launched our new product Cluster One. It’s a very big project that heavily depends on a community of people being involved and I would love to get your feedback on it. At Cluster One we are trying to help advance science by building the world's largest AI supercomputer.

We understand how much computing power is wasted every day (around 10 billions hours!) and we feel that with our expertise, and if we all join together, we could really make a difference in advancing scientific research.

The product has just launched this week and so I would love your feedback on the site to understand if everything makes sense and would it be something you would want to try, and if not what would stop you?
 
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#3
Hi,
I have just visited your website. But I don't see anything other than a movement. As I love computing and has built AI based programs on python. Yeah so many cpu cycles are wasted for redundancy in so many servers.

But if it's a product that solves this issue.. how can I test it in my machine. I like the idea of cluster computing. I have done so many models like that using Amazon AWS. But I'm just asking. What sets you better than other solutions which already exist now. And main link appears to be broken. I have tried clicking on the logo of you website after visiting ur website which should get me to home page but appears to be broken..

I am a computer science student. So just tell me how can we make use of it to make things better.

Currently I'm working on a chat bot for telegram which runs on raspberry pi, but it's slow may be your product can help me solve that issue :)

Hi everyone,

I’m the founder of Good Ai Lab and we have just launched our new product Cluster One. It’s a very big project that heavily depends on a community of people being involved and I would love to get your feedback on it. At Cluster One we are trying to help advance science by building the world's largest AI supercomputer.

We understand how much computing power is wasted every day (around 10 billions hours!) and we feel that with our expertise, and if we all join together, we could really make a difference in advancing scientific research.

The product has just launched this week and so I would love your feedback on the site to understand if everything makes sense and would it be something you would want to try, and if not what would stop you?
 
#4
@Arjun Chandran , @Abhiram Shibu - thank you for your responses. To address the comments, I've recently written a blog post about why we have created Cluster One.

Feel free to read my article on Medium: Announcing Cluster One, the largest AI Supercomputer

OR

To wrap it up for you:

AI as critical as in medical research

AI will be the key to unlocking new scientific discoveries. A year ago, top cancer researchers reported to President Obama about the state of cancer research, and most of their recommendations mentioned large scale computing as a way to move the industry forward.


AI is not affordable for every company and is exclusive because of:
  • algorithms and science is still limited
  • knowledge and expertise to use it is rare
  • infrastructure is hard to build and costly to operate

We see ourselves as solving a part of that problem. Organizations such as the Allen institute are advancing and spreading algorithms. Companies such as Andrew Ng’s deeplearning.ai are trying to spread deep learning skills.
What’s missing in that picture is spreading affordable infrastructure and tools. That’s why we are launching Cluster One.
We want to enable researchers to address life-threatening problems, by scaling AI to the next level.


It is important to understand what size we need to reach before being able to do something meaningful.
For example, take Diabetic Retinopathy, a disease that affects people with diabetes, and can ultimately cause blindness. It affects nearly 100 Million people in the world.

For the sake of understanding what it would take to offer a screening solution through AI, let us assume the following.
  • explore 100 ideas
  • run 50 experiments per idea
  • run each of them for a week of computation, on 50 machines

That’s a total of 42MM compute hours.

That would cost around $10MM on the public cloud (eg: on AWS’s c4.2xlarge), or several dozens of millions of upfront investment for a private infrastructure.

Or it could be provided by 15,000 contributors who provide 8 hours of compute a day for a year, on recent computers.

That’s why we believe in the power of distributed computing and we’re on a mission to scale AI to enable researchers push science further. Feel free to reach out to me if you have any further questions or would like to know more about the movement. Or if you want to help, sign up to join Cluster One community.
 

Arjun Chandran

Bronze I
Staff member
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#5
@Arjun Chandran , @Abhiram Shibu- thank you for your responses. To address the comments, I've recently written a blog post about why we have created Cluster One.

Feel free to read my article on Medium: Announcing Cluster One, the largest AI Supercomputer

OR

To wrap it up for you:

AI as critical as in medical research

AI will be the key to unlocking new scientific discoveries. A year ago, top cancer researchers reported to President Obama about the state of cancer research, and most of their recommendations mentioned large scale computing as a way to move the industry forward.


AI is not affordable for every company and is exclusive because of:
  • algorithms and science is still limited
  • knowledge and expertise to use it is rare
  • infrastructure is hard to build and costly to operate

We see ourselves as solving a part of that problem. Organizations such as the Allen institute are advancing and spreading algorithms. Companies such as Andrew Ng’s deeplearning.ai are trying to spread deep learning skills.
What’s missing in that picture is spreading affordable infrastructure and tools. That’s why we are launching Cluster One.
We want to enable researchers to address life-threatening problems, by scaling AI to the next level.


It is important to understand what size we need to reach before being able to do something meaningful.
For example, take Diabetic Retinopathy, a disease that affects people with diabetes, and can ultimately cause blindness. It affects nearly 100 Million people in the world.

For the sake of understanding what it would take to offer a screening solution through AI, let us assume the following.
  • explore 100 ideas
  • run 50 experiments per idea
  • run each of them for a week of computation, on 50 machines

That’s a total of 42MM compute hours.

That would cost around $10MM on the public cloud (eg: on AWS’s c4.2xlarge), or several dozens of millions of upfront investment for a private infrastructure.

Or it could be provided by 15,000 contributors who provide 8 hours of compute a day for a year, on recent computers.

That’s why we believe in the power of distributed computing and we’re on a mission to scale AI to enable researchers push science further. Feel free to reach out to me if you have any further questions or would like to know more about the movement. Or if you want to help, sign up to join Cluster One community.
@Abhiram Shibu any thoughts on this? And are you with us?
 

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